Mercury | Hiring | Data Engineer | San Francisco, CA | BigDataKB.com | 6 Oct 2022

Job Location: San Francisco, CA

SF, NY, Toronto, Portland, or remote
Full-time
Mercury

In the 1880s, Herman Hollerith noticed the US Census was taking over 8 years to calculate. To solve this, he invented a tabulating machine using punch cards that dramatically sped up the process and served as the foundation for innovation in high quality data gathering.

Weโ€™re looking for our first Data Engineer who can help us build our high quality data engine that informs how we invest in and build Mercuryโ€™s future. Youโ€™ll be early to building a data-informed culture across Mercury so that we can all determine whatโ€™s happening, react quickly, and invest intelligently.

Here are some things youโ€™ll do on the job:

  • Partner with leadership, engineers, and data scientists to understand data needs and build systems that deliver high quality and reliable data.
  • Own and maintain the data systems that extract, transform, and load data into internal and external tooling.
  • Apply proven expertise and build high-performance scalable data warehouses.
  • Design, build, and launch efficient & reliable data pipelines to move and transform data (both large and small amounts).
  • Design and develop new systems in partnership with software engineers to enable quick and easy consumption of data.

You should:

  • Have 2+ years of experience working with analytics teams on building high quality and reliable data infrastructure.
  • Be able to navigate from architecture and implementation decisions related to data infrastructure to guide teams towards building reliable and accurate pipelines and company-critical data sets.
  • Have familiarity with postgres backend data, Snowflake, and data transformation tools like dbt.
  • Value quality in data tools, testing, and innovation.




Apply Here

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